Eigen::NumericalDiff< Functor_, mode > Class Template Reference

#include <NumericalDiff.h>

Inheritance diagram for Eigen::NumericalDiff< Functor_, mode >:

Public Types
enum	{ InputsAtCompileTime = Functor::InputsAtCompileTime , ValuesAtCompileTime = Functor::ValuesAtCompileTime }
typedef Functor_	Functor
typedef Functor::Scalar	Scalar
typedef Functor::InputType	InputType
typedef Functor::ValueType	ValueType
typedef Functor::JacobianType	JacobianType

Public Member Functions
	NumericalDiff (Scalar _epsfcn=0.)
	NumericalDiff (const Functor &f, Scalar _epsfcn=0.)
template<typename T0 >
	NumericalDiff (const T0 &a0)
template<typename T0 , typename T1 >
	NumericalDiff (const T0 &a0, const T1 &a1)
template<typename T0 , typename T1 , typename T2 >
	NumericalDiff (const T0 &a0, const T1 &a1, const T2 &a2)
int	df (const InputType &_x, JacobianType &jac) const

Private Member Functions
NumericalDiff &	operator= (const NumericalDiff &)

Private Attributes
Scalar	epsfcn

Detailed Description

template<typename Functor_, NumericalDiffMode mode = Forward>
class Eigen::NumericalDiff< Functor_, mode >

This class allows you to add a method df() to your functor, which will use numerical differentiation to compute an approximate of the derivative for the functor. Of course, if you have an analytical form for the derivative, you should rather implement df() by yourself.

More information on http://en.wikipedia.org/wiki/Numerical_differentiation

Currently only "Forward" and "Central" scheme are implemented.

Member Typedef Documentation

Functor

template<typename Functor_ , NumericalDiffMode mode = Forward>

typedef Functor_ Eigen::NumericalDiff< Functor_, mode >::Functor

InputType

template<typename Functor_ , NumericalDiffMode mode = Forward>

typedef Functor::InputType Eigen::NumericalDiff< Functor_, mode >::InputType

JacobianType

template<typename Functor_ , NumericalDiffMode mode = Forward>

typedef Functor::JacobianType Eigen::NumericalDiff< Functor_, mode >::JacobianType

Scalar

template<typename Functor_ , NumericalDiffMode mode = Forward>

typedef Functor::Scalar Eigen::NumericalDiff< Functor_, mode >::Scalar

ValueType

template<typename Functor_ , NumericalDiffMode mode = Forward>

typedef Functor::ValueType Eigen::NumericalDiff< Functor_, mode >::ValueType

Member Enumeration Documentation

anonymous enum

template<typename Functor_ , NumericalDiffMode mode = Forward>

anonymous enum

Enumerator
InputsAtCompileTime
ValuesAtCompileTime

{ InputsAtCompileTime = Functor::InputsAtCompileTime, ValuesAtCompileTime = Functor::ValuesAtCompileTime };

Constructor & Destructor Documentation

NumericalDiff() [1/5]

template<typename Functor_ , NumericalDiffMode mode = Forward>

Eigen::NumericalDiff< Functor_, mode >::NumericalDiff ( Scalar  _epsfcn = 0. )

inline

: Functor(), epsfcn(_epsfcn) {}

NumericalDiff() [2/5]

template<typename Functor_ , NumericalDiffMode mode = Forward>

Eigen::NumericalDiff< Functor_, mode >::NumericalDiff ( const Functor &  f, Scalar  _epsfcn = 0.  )

inline

: Functor(f), epsfcn(_epsfcn) {}

NumericalDiff() [3/5]

template<typename Functor_ , NumericalDiffMode mode = Forward>

template<typename T0 >

Eigen::NumericalDiff< Functor_, mode >::NumericalDiff ( const T0 &  a0 )

inline

: Functor(a0), epsfcn(0) {}

NumericalDiff() [4/5]

template<typename Functor_ , NumericalDiffMode mode = Forward>

template<typename T0 , typename T1 >

Eigen::NumericalDiff< Functor_, mode >::NumericalDiff ( const T0 &  a0, const T1 &  a1  )

inline

: Functor(a0, a1), epsfcn(0) {}

NumericalDiff() [5/5]

template<typename Functor_ , NumericalDiffMode mode = Forward>

template<typename T0 , typename T1 , typename T2 >

Eigen::NumericalDiff< Functor_, mode >::NumericalDiff ( const T0 &  a0, const T1 &  a1, const T2 &  a2  )

inline

: Functor(a0, a1, a2), epsfcn(0) {}

Member Function Documentation

df()

template<typename Functor_ , NumericalDiffMode mode = Forward>

int Eigen::NumericalDiff< Functor_, mode >::df ( const InputType &  _x, JacobianType &  jac  ) const

inline

return the number of evaluation of functor

                                                       {
    using std::abs;
    using std::sqrt;
    /* Local variables */
    Scalar h;
    int nfev = 0;
    const typename InputType::Index n = _x.size();
    const Scalar eps = sqrt(((std::max)(epsfcn, NumTraits<Scalar>::epsilon())));
    ValueType val1, val2;
    InputType x = _x;
    // TODO : we should do this only if the size is not already known
    val1.resize(Functor::values());
    val2.resize(Functor::values());
 
    // initialization
    switch (mode) {
      case Forward:
        // compute f(x)
        Functor::operator()(x, val1);
        nfev++;
        break;
      case Central:
        // do nothing
        break;
      default:
        eigen_assert(false);
    };
 
    // Function Body
    for (int j = 0; j < n; ++j) {
      h = eps * abs(x[j]);
      if (h == 0.) {
        h = eps;
      }
      switch (mode) {
        case Forward:
          x[j] += h;
          Functor::operator()(x, val2);
          nfev++;
          x[j] = _x[j];
          jac.col(j) = (val2 - val1) / h;
          break;
        case Central:
          x[j] += h;
          Functor::operator()(x, val2);
          nfev++;
          x[j] -= 2 * h;
          Functor::operator()(x, val1);
          nfev++;
          x[j] = _x[j];
          jac.col(j) = (val2 - val1) / (2 * h);
          break;
        default:
          eigen_assert(false);
      };
    }
    return nfev;
  }

References abs(), Eigen::Central, eigen_assert, CRBond_Bessel::eps, Eigen::NumericalDiff< Functor_, mode >::epsfcn, Eigen::Forward, j, max, n, sqrt(), Functor< Scalar_, NX, NY >::values(), and plotDoE::x.

Referenced by test_central(), and test_forward().

operator=()

template<typename Functor_ , NumericalDiffMode mode = Forward>

NumericalDiff& Eigen::NumericalDiff< Functor_, mode >::operator= ( const NumericalDiff< Functor_, mode > &  )

private

Member Data Documentation

epsfcn

template<typename Functor_ , NumericalDiffMode mode = Forward>

Scalar Eigen::NumericalDiff< Functor_, mode >::epsfcn

private

Referenced by Eigen::NumericalDiff< Functor_, mode >::df().

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The documentation for this class was generated from the following file:

• NumericalDiff.h